Stable isotopic compositions of precipitation in China

SJ (Sanjiang)133.347.35554632.8−80.1−207.3−38.347.13−10.42−28.21−4.746.360.588**0.4257.29−6.718.79 HL (Hailun)126.9347.452364692.5−92.8−229.6−50.152.92−12.52−29.47−6.856.830.781**0.418*7.712.588.70 CB (Changbaishan)128.1142.4738.17033.8−74.7−193.8−9.735.02−8.56−22.333.105.020.542**0.265*6.40−22.048.78North China (NC)

SY (Shenyang)123.3741.52495548.5−62.7−120.4−13.024.35−8.95−17.23−0.533.530.230−0.2046.25−5.768.70 BJ (Beijing)115.4339.9612484675.3−69.6−190.5−30.640.39−9.16−24.33−4.634.920.814**0.501**7.943.928.77 YC (Yucheng)116.5736.832253613.3−54.2−150.8−6.328.78−6.36−19.07−0.513.710.1100.0187.53−6.568.54 CW (Changwu)107.6835.24120045710.3−55.9−91.717.631.04−7.35−11.683.454.620.137−0.2916.50−6.688.67 FQ (Fengqiu)114.3335.0167.551514.0−57.3−103.4−9.924.74−7.37−14.381.053.78−0.280−0.4426.24−9.198.50Southern China (SC)

CS (Changshu)120.4231.333.194417.0−45.0−75.0−10.617.78−6.75−9.58−3.011.89−0.623**−0.2958.7713.968.48 TY (Taoyuan)111.4428.93106138217.3−34.7−86.81.822.99−5.93−11.87−2.122.56−0.045−0.609**8.6317.108.55 YT (Yingtan)116.5628.1245173618.4−45.0−103.5−6.720.98−5.59−12.90−1.325.60−0.148−0.0986.41−8.258.41 HT (Huitong)109.6126.8554196816.7−36.9−93.314.825.31−5.88−11.86−1.142.96−0.212−0.650**8.0811.478.55 QY (Qianyanzhou)115.0326.4476.4138317.9−35.4−74.4−1.120.04−4.54−8.350.382.48−0.299−0.1717.34−1.988.50 HJ (Huanjiang)108.3324.74400141719.3−38.7−81.416.132.43−6.16−11.42−0.583.63−0.679*−0.3658.8917.318.43 DH (Dinghushan)112.5523.1690180522.2−25.9−65.836.728.84−2.75−9.567.334.25−0.523*−0.558*6.53−8.358.39 YG (Yanting)105.4631.2742084116.6−42.6−91.045.440.55−5.55−12.369.155.68−0.360−0.3506.77−2.308.50 AL (Ailaoshan)101.0324.552481148411.6−86.9−123.34.140.11−12.19−16.41−0.024.93−0.620**−0.632**8.0911.948.37 BN (Xishuangbanna)101.2621.93560137122.4−45.0−68.4−21.816.74−6.94−9.74−3.442.27−0.367−0.1367.827.008.25Northwestern China (NW)

FK (Fukang)87.9344.294601677.5−67.6−183.4−15.154.07−9.87−24.64−2.066.790.891**0.310*7.838.868.70 CL (Cele)80.7337.0213065112.9−4.2−87.427.340.37−1.47−12.202.805.310.674*0.2577.546.878.97 LZ (Linze)100.1339.3513751279.0−36.1−175.81.863.15−6.21−24.421.608.150.910**0.3467.512.768.90 SP (Shapotou)10537.28135012610.9−52.6−90.721.828.18−7.16−12.843.324.040.397*−0.3307.11−1.168.67 AS (Ansai)109.3236.86108346010.1−58.2−106.825.227.42−8.11−14.814.413.730.202−0.307*7.06−0.628.66 ED (Erdos)80.7337.0213062796.9−43.8−85.522.029.54−6.06−10.873.814.050.353−0.4107.12−0.238.92 NM (Naiman)120.742.9337.282897.1−67.1−213.0−34.539.39−8.65−26.04−4.255.030.772**0.3627.71−1.288.71Tibetan Plateau (TP)

LS (Lhasa)91.2129.4136884078.5−110.9−169.938.553.20−15.02−22.650.266.52−0.287−0.2548.0410.868.30 HB (Haibei)101.3137.563280458−0.1−56.2−133.3−6.935.38−8.10−17.20−1.404.520.430*0.2097.624.659.12 MX (Maoxian)103.931.718267199.7−49.5−83.38.524.37−7.77−11.980.313.16−0.088−0.2017.568.198.76 GG (Gonggashan)10229.58295017045.1−76.5−147.81.430.86−10.82−19.50−2.353.73−0.496**−0.424**8.1012.568.73

[i] ^aMean precipitation (P) and temperature (T) values during respective observation periods.

[ii] ^bδ-values are averaged by monthly precipitation amount, using the equation $\bar{δ_{p}} = \sum_{i = 1}^{n} δ \times P_{i} / \sum_{i = 1}^{n} P_{i}$ .

[iii] * or ** stand for significance at 0.05 or 0.01 level, respectively. SD, standard deviation; r, linear correlation coefficients between δ¹⁸O and temperature (or precipitation amount); S_T, theoretical slope of LMWL.

Distributions of (δ_s–δ_w) values. The δ_s and δ_w denote the un-weighted means of the summer (May–Oct.) and winter months (Nov.–Apr.), respectively. Group I, II and III all belong to the inner continental climate, indicating a major temperature contribution to the δ¹⁸O variation. Group IV and V are generally located in the middle and southeastern parts of China, and both the precipitation and temperature may contribute to the small (δ_s–δ_w) values. Group VI and VII distribute to latitude <30°N, and with a precipitation contribution.

Temporal variations of δ¹⁸O during 2005–2010. Large, small and mediate seasonal fluctuations of δ¹⁸O are found in the northern (NW and NE), southern (SC) and NC regions, respectively. A ‘V’-shaped δ¹⁸O pattern is found at SC, while a reverse ‘V’-shaped pattern is found at NE and NW.

Linear δD–δ¹⁸O relationships (CMWL) based on all the CHNIP precipitation measurements from 2005 to 2010 (grey crosses). Seasonal amount weighted δ-values (triangle–spring, circle–summer, rectangle–autumn and diamond–winter) of different regions (blue–NE, yellow–NC, green–SC, red–NW and purple–TP) are also given for reference. The arrows indicate potential vapour source conditions (McGuire and McDonnell, 2007).

Seasonal variations of δ¹⁸O (precipitation amount weighted), temperature and precipitation amount (averages during the respective observation period) for the 10 selected CHNIP stations. The seasonal effect is more pronounced for continental sites with strong temperature variations.

Table 2. Stepwise regression models for CHNIP stations

RegionStationNon-linear stepwise regression modelsAdjusted R²p

NESJδ¹⁸O=−13.379+0.239T0.3110.005HLδ¹⁸O=−16.876+0.331T0.5960.000CBδ¹⁸O=−7.559+0.469T−0.549Wp0.3490.006NCSYδ¹⁸O=−99.930−0.003Wd²+0.986Wd0.2100.015BJδ¹⁸O=−10.417+0.747T−0.025Wp²−0.035S0.7070.050YCδ¹⁸O=−20.479+0.084Wd0.2310.007CWδ¹⁸O=253.076−0.002RH²−0.285Vp0.5300.029FQδ¹⁸O=2.552−0.001RH²0.1830.055SCCSδ¹⁸O=−7.564−0.006T²+0.023S0.5860.011TYδ¹⁸O=2045.727−681.929logVp−0.013Wp²0.5860.001YTδ¹⁸O=−4.138−0.018S+1.963Ws²−0.008P0.1580.027HTδ¹⁸O=1848.366−0.015Wp²−620.738logVp0.5410.028QYδ¹⁸O=3170.993−0.015Wp²−1055.79logVp0.2880.012HJδ¹⁸O=2.783−0.059S0.5190.017DHδ¹⁸O=−3629.392+1209.223logVp0.3520.002YGδ¹⁸O=−3.218+0.06T²−0.065Wp²0.4190.025ALδ¹⁸O=−12.074−0.518Wp+0.035Wd+0.031S0.7510.040BNδ¹⁸O=−11.788+0.0002Wd²0.3450.043NWFKδ¹⁸O=−8.805+0.220T−0.001RH²0.8100.016CLδ¹⁸O=−1252.324+0.037T²+1.436Vp−(9.133×10⁻⁵)Wd²0.8950.016LZδ¹⁸O=−16.841+0.609T0.8220.000SPδ¹⁸O=−16.582+10.146logT−0.092P0.3280.014ASδ¹⁸O=−1.991−0.033P+0.226T−0.107RH0.4250.013NMδ¹⁸O=−14.175+0.303T0.5590.000TPLSδ¹⁸O=−38.857+18.078Ws0.3680.000HBδ¹⁸O=−9.355+0.243T0.1460.040MXδ¹⁸O=36.879−0.090Wd−0.455RH+0.530T−0.029Wp²0.7260.010GGδ¹⁸O=23.482−0.027Wp²−0.343RH0.4030.007

[i] P, precipitation (mm); T, surface air temperature (°C); Vp, vapour pressure (hPa); RH, relative humidity (%); Wp, water pressure (hPa); S, sunshine duration (h); Ws, wind speed (m/s); Wd, wind direction (°).

Table 3. Stepwise regression models for GNIP stations

RegionStationNon-linear stepwise regression modelsAdjusted R²p

NEQiqiharδ¹⁸O=−17.138+0.418T0.6060.000Haerbinδ¹⁸O=−18.614+0.039S0.2400.004Changchunδ¹⁸O=−11.847−0.007T²+0.309T0.8290.006NCTianjinδ¹⁸O=9.449−0.02P−0.012T²+0.520T+0.004RH²−0.590RH0.6130.035Shijiazhuangδ¹⁸O=−11.3−0.015T²+0.469T+(4.41×10⁻⁵)S²0.2840.048Yantaiδ¹⁸O=24.571+0.006RH²−0.873RH0.2390.038Zhengzhouδ¹⁸O=−25.117+0.504Ws²+7.312logS0.1760.035Xianδ¹⁸O=0.122−0.001RH²0.1590.001SCNanjingδ¹⁸O=1266.466−0.144RH−0.007Wp²−419.209logVp0.4030.027Wuhanδ¹⁸O=4163.429−0.017T²−1384.699logVp−0.013P0.4170.007Changshaδ¹⁸O=3742.282−0.02Wp²−0.001RH²−1242.53logVp0.5300.003Fuzhouδ¹⁸O=4078.656−0.013P−0.668T−1355.431logVp0.3510.001Zunyiδ¹⁸O=4109.289−0.954Wp−1384.216logVp0.6010.000Guiyangδ¹⁸O=3901.415−0.03Wp²−1322.441logVp+1.996logWd0.5760.023Guilinδ¹⁸O=2277.891−0.015T²−758.678logVp−1.445logP0.5710.046Liuzhouδ¹⁸O=3052.851−0.017Wp²−1016.873logVp0.4690.012Chengduδ¹⁸O=4970.782−0.023Wp²−1666.96logVp0.5530.000Kunmingδ¹⁸O=5.200−0.002RH²−0.287T+1.314Ws0.6450.011Guangzhouδ¹⁸O=0.078−2.403logP0.2370.008Haikouδ¹⁸O=−2075.433+684.554logVp−0.016Wd²+0.176RH0.5340.038NWBaotouδ¹⁸O=−22.627+0.057S0.3480.000Hetianδ¹⁸O=−4842.976+0.045T²+0.036Wd²+1640.639logVp0.7930.028Lanzhouδ¹⁸O=−13.705+0.447T0.4750.000Wulumuqiδ¹⁸O=−14.101+0.428T−0.146Wd0.7370.035Yinchuanδ¹⁸O=−11.567−0.019T²+0.631T0.4700.022Zhangyeδ¹⁸O=−2419.214+0.662T+820.415logVp0.7050.042TPLhasaδ¹⁸O=886.838−0.002Vp²0.2830.001

Reconstruction of monthly δ¹⁸O time series for the period of 1986–2009, based on the regression model established for Wulumuqi station (δ¹⁸O=−14.101+0.428T−0.146Wd). With the exception of a few values during extreme cold and hot months, the reconstructions depict the seasonal cycle of δ¹⁸O. The calculated δ¹⁸O values for most spring and autumn seasons are very close to the observations.

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DOI: https://doi.org/10.3402/tellusb.v66.22567 | Journal eISSN: 1600-0889

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Language: English

Page range: 22567 - 22567

Submitted on: Aug 8, 2013

Accepted on: Feb 12, 2014

Published on: Jan 1, 2014

Published by: Stockholm University Press

In partnership with: Paradigm Publishing Services

Keywords:

δD,

δ¹⁸O,

CHNIP,

GNIP,

environmental controls,

multiple non-linear stepwise regressions

© 2014 Jianrong Liu, Xianfang Song, Guofu Yuan, Xiaomin Sun, Lihu Yang, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 66 (2014): Issue 1

Stable isotopic compositions of precipitation in China

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